text: import h5py
  import numpy as np
  
  
  
  pathGTTrain = "CLSA_CFA_GRAHAM_GoodAndUsable.hdf5"
  with h5py.File(pathGTTrain, "r") as f:  # "with" close the file after its nested commands
      everything = f["gt"][:][:]
      cog = f["gt"][:][:, 28]
      mem = f["gt"][:][:, 29]
      spd = f["gt"][:][:, 30]
      exe = f["gt"][:][:, 31]
      stp = f["gt"][:][:, 24]
  
  max = 100
  min = -230
  cog_new = (100-0)/(max-min)*(cog-max)+100
  #
  #
  max = 0
  min = 10
  mem_new = (100-0)/(max-min)*(mem-max)+100
  #
  max = 0
  min = 100
  spd_new = (100-0)/(max-min)*(spd-max)+100
  #
  max = 0
  min = 32
  exe_new = (100-0)/(max-min)*(exe-max)+100
  #
  max = 0.5
  min = 2.5
  stp_new = (100-0)/(max-min)*(stp-max)+100
  
  
  everything[:, 28] = cog_new
  everything[:, 29] = mem_new
  everything[:, 30] = spd_new
  everything[:, 31] = exe_new
  everything[:, 24] = stp_new
  
  print('train')
  data = everything[0:18000]
  print("age mean" + str(np.mean(data[:, 1])) + '||' "std" + str(np.std(data[:, 1])))
  print("bmi mean" + str(np.mean(data[:, 35])) + '||' "std" + str(np.std(data[:, 35])))
  print("sbp mean" + str(np.mean(data[:, 32])) + '||' "std" + str(np.std(data[:, 32])))
  print("dpb mean" + str(np.mean(data[:, 33])) + '||' "std" + str(np.std(data[:, 33])))
  print("exec mean" + str(np.mean(data[:, 31])) + '||' "std" + str(np.std(data[:, 31])))
  print("speed mean" + str(np.mean(data[:, 30])) + '||' "std" + str(np.std(data[:, 30])))
  print("mem mean" + str(np.mean(data[:, 29])) + '||' "std" + str(np.std(data[:, 29])))
  print("inhib mean" + str(np.mean(data[:, 24])) + '||' "std" + str(np.std(data[:, 24])))
  print("cog mean" + str(np.mean(data[:, 28])) + '||' "std" + str(np.std(data[:, 28])))
  
  print('val')
  data = everything[18000:21860]
  print("age mean" + str(np.mean(data[:, 1])) + '||' "std" + str(np.std(data[:, 1])))
  print("bmi mean" + str(np.mean(data[:, 35])) + '||' "std" + str(np.std(data[:, 35])))
  print("sbp mean" + str(np.mean(data[:, 32])) + '||' "std" + str(np.std(data[:, 32])))
  print("dpb mean" + str(np.mean(data[:, 33])) + '||' "std" + str(np.std(data[:, 33])))
  print("exec mean" + str(np.mean(data[:, 31])) + '||' "std" + str(np.std(data[:, 31])))
  print("speed mean" + str(np.mean(data[:, 30])) + '||' "std" + str(np.std(data[:, 30])))
  print("mem mean" + str(np.mean(data[:, 29])) + '||' "std" + str(np.std(data[:, 29])))
  print("inhib mean" + str(np.mean(data[:, 24])) + '||' "std" + str(np.std(data[:, 24])))
  print("cog mean" + str(np.mean(data[:, 28])) + '||' "std" + str(np.std(data[:, 28])))
  
  print('test')
  data = everything[21860:]
  print("age mean" + str(np.mean(data[:, 1])) + '||' "std" + str(np.std(data[:, 1])))
  print("bmi mean" + str(np.mean(data[:, 35])) + '||' "std" + str(np.std(data[:, 35])))
  print("sbp mean" + str(np.mean(data[:, 32])) + '||' "std" + str(np.std(data[:, 32])))
  print("dpb mean" + str(np.mean(data[:, 33])) + '||' "std" + str(np.std(data[:, 33])))
  print("exec mean" + str(np.mean(data[:, 31])) + '||' "std" + str(np.std(data[:, 31])))
  print("speed mean" + str(np.mean(data[:, 30])) + '||' "std" + str(np.std(data[:, 30])))
  print("mem mean" + str(np.mean(data[:, 29])) + '||' "std" + str(np.std(data[:, 29])))
  print("inhib mean" + str(np.mean(data[:, 24])) + '||' "std" + str(np.std(data[:, 24])))
  print("cog mean" + str(np.mean(data[:, 28])) + '||' "std" + str(np.std(data[:, 28])))
  
  import matplotlib.pyplot as plt
  n, bins, patches = plt.hist(x=cog, bins='auto', color='#0504aa',
                              alpha=0.7, rwidth=0.85)
  plt.grid(axis='y', alpha=0.75)
  plt.xlabel('Value')
  plt.ylabel('Frequency')
  plt.title('My Very Own Histogram')
  plt.text(23, 45, r'$\mu=15, b=3$')
  maxfreq = n.max()
  # Set a clean upper y-axis limit.
  plt.ylim(ymax=np.ceil(maxfreq / 10) * 10 if maxfreq % 10 else maxfreq + 10)
  plt.show()
  
  print(1)
  with h5py.File(pathGTTrain, "r+") as f:
      f["gt"][...] = everything
  